GitHub topics: context-aware-ai
Md-Emon-Hasan/MediGenius
🩺 Medical consultation chatbot built with LangGraph and Streamlit. It mimics a human doctor’s tone while answering health-related queries using a layered fallback pipeline: starts with LLM-based reasoning, falls back to a vector database of medical PDFs (RAG), then queries Wikipedia, and finally uses DuckDuckGo for external search when needed.
Language: Jupyter Notebook - Size: 12.2 MB - Last synced at: 4 days ago - Pushed at: 4 days ago - Stars: 1 - Forks: 0
apatni24/VisionQA
Context-aware tool for automated BDD test generation and execution using RAG, VectorDB, and LLaMA.
Language: Python - Size: 1.2 MB - Last synced at: 11 days ago - Pushed at: 16 days ago - Stars: 0 - Forks: 0
prdepyadv/ClassifyXR.ai
The Customer Support Ticket Classification and Response System combines advance AI models with RAG to automate and elevate ticket categorisation and response generation. By leveraging multi-model integration, sentiment analysis, urgency detection, and vector-based retrieval, it delivers precise, context-aware responses and actionable insights.
Language: Python - Size: 3.68 MB - Last synced at: 2 months ago - Pushed at: 8 months ago - Stars: 1 - Forks: 0
